Abortion by Year

Induced Abortions in Years (2019)

url = "https://www.health.ny.gov/statistics/vital_statistics/2019/table21.htm"
url1= "https://www.health.ny.gov/statistics/vital_statistics/2019/table07.htm"
induced_abortion_2019 = 
  read_html(url) %>%
  html_table(header = FALSE) %>%
  first() %>%
  janitor::clean_names()
live_birth_2019 = 
  read_html(url1) %>%
  html_table(header = FALSE) %>%
  first() %>%
  janitor::clean_names()

data cleaning

Renaming

created regions based on this website: https://statejobs.ny.gov/assets/help/regionMapText.cfm

renaming counties into regions.

rename_ia_2019= clean_ia_2019 %>% 
  transform(borough = gsub(pattern = "Albany|Columbia|Fulton|Greene|Montgomery|Rensselaer|Saratoga|Schenectady|Schoharie|Warren|Washington", replacement = "Saratoga", borough)) %>%
  transform(borough = gsub(pattern = "Franklin|Clinton|Essex/Hamilton|Hamilton/Essex", replacement = "Eastern Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Herkimer|Jefferson|Lewis|Oneida|Oswego|St Lawrence", replacement = "Western Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Broome|Cayuga|Chenango|Cortland|Madison|Onondaga|Otsego|Tioga|Tompkins", replacement = "Central New York", borough)) %>% 
  transform(borough=gsub(pattern="Chemung|Genesee|Livingston|Monroe|Ontario|Schuyler|Seneca|Steuben|Wayne|Yates",replacement="Finger Lakes", borough)) %>% 
  transform(borough=gsub(pattern="Allegany|Cattaraugus|Chautauqua|Erie|Niagara|Orleans|Wyoming",replacement="Western New York", borough)) %>% 
  transform(borough=gsub(pattern="Delaware|Dutchess|Orange|Putnam|Sullivan|Ulster",replacement="Hudson Valley", borough)) %>% 
  transform(borough=gsub(pattern="Rockland|Westchester", replacement="Westchester/Rockland", borough)) %>% 
  transform(borough=gsub(pattern="Suffolk|Nassau", replacement="Long Island", borough)) %>% 
  group_by(borough, year) %>% 
  summarize(total_rate= sum(total))

## `summarise()` has grouped output by 'borough'. You can override using the
## `.groups` argument.

rename_lb_2019= clean_lb_2019 %>% 
  transform(borough = gsub(pattern = "Albany|Columbia|Fulton|Greene|Montgomery|Rensselaer|Saratoga|Schenectady|Schoharie|Warren|Washington", replacement = "Saratoga", borough)) %>%
  transform(borough = gsub(pattern = "Franklin|Clinton|Essex|Hamilton", replacement = "Eastern Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Herkimer|Jefferson|Lewis|Oneida|Oswego|St Lawrence", replacement = "Western Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Broome|Cayuga|Chenango|Cortland|Madison|Onondaga|Otsego|Tioga|Tompkins", replacement = "Central New York", borough)) %>% 
  transform(borough=gsub(pattern="Chemung|Genesee|Livingston|Monroe|Ontario|Schuyler|Seneca|Steuben|Wayne|Yates",replacement="Finger Lakes", borough)) %>% 
  transform(borough=gsub(pattern="Allegany|Cattaraugus|Chautauqua|Erie|Niagara|Orleans|Wyoming",replacement="Western New York", borough)) %>% 
  transform(borough=gsub(pattern="Delaware|Dutchess|Orange|Putnam|Sullivan|Ulster",replacement="Hudson Valley", borough)) %>% 
  transform(borough=gsub(pattern="Rockland|Westchester", replacement="Westchester/Rockland", borough)) %>% 
  transform(borough=gsub(pattern="Suffolk|Nassau", replacement="Long Island", borough)) %>% 
  group_by(borough, year) %>% 
  summarize(total_rate= sum(total))

## `summarise()` has grouped output by 'borough'. You can override using the
## `.groups` argument.

Merging

merged_2019=
  full_join(rename_lb_2019,rename_ia_2019, by="borough") %>%
  janitor::clean_names() %>%
  mutate(total = (total_rate_y / total_rate_x)*1000) %>% 
  select(total, year_x)

## Adding missing grouping variables: `borough`

Induced Abortions in Years (2018)

url = "https://www.health.ny.gov/statistics/vital_statistics/2018/table21.htm"
url1 = "https://www.health.ny.gov/statistics/vital_statistics/2018/table07.htm"
induced_abortion_2018 = 
  read_html(url) %>%
  html_table(header = FALSE) %>%
  first() %>%
  janitor::clean_names()
live_birth_2018 = 
  read_html(url1) %>%
  html_table(header = FALSE) %>%
  first() %>%
  janitor::clean_names()

data cleaning

Renaming

renaming counties into regions.

rename_lb_2018= clean_lb_2018 %>% 
  transform(borough = gsub(pattern = "Albany|Columbia|Fulton|Greene|Montgomery|Rensselaer|Saratoga|Schenectady|Schoharie|Warren|Washington", replacement = "Saratoga", borough)) %>%
  transform(borough = gsub(pattern = "Franklin|Clinton|Essex|Hamilton", replacement = "Eastern Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Herkimer|Jefferson|Lewis|Oneida|Oswego|St Lawrence", replacement = "Western Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Broome|Cayuga|Chenango|Cortland|Madison|Onondaga|Otsego|Tioga|Tompkins", replacement = "Central New York", borough)) %>% 
  transform(borough=gsub(pattern="Chemung|Genesee|Livingston|Monroe|Ontario|Schuyler|Seneca|Steuben|Wayne|Yates",replacement="Finger Lakes", borough)) %>% 
  transform(borough=gsub(pattern="Allegany|Cattaraugus|Chautauqua|Erie|Niagara|Orleans|Wyoming",replacement="Western New York", borough)) %>% 
  transform(borough=gsub(pattern="Delaware|Dutchess|Orange|Putnam|Sullivan|Ulster",replacement="Hudson Valley", borough)) %>% 
  transform(borough=gsub(pattern="Rockland|Westchester", replacement="Westchester/Rockland", borough)) %>% 
  transform(borough=gsub(pattern="Suffolk|Nassau", replacement="Long Island", borough)) %>% 
  group_by(borough, year) %>% 
  summarize(total_rate= sum(total))

## `summarise()` has grouped output by 'borough'. You can override using the
## `.groups` argument.

rename_ia_2018= clean_ia_2018 %>% 
  transform(borough = gsub(pattern = "Albany|Columbia|Fulton|Greene|Montgomery|Rensselaer|Saratoga|Schenectady|Schoharie|Warren|Washington", replacement = "Saratoga", borough)) %>%
  transform(borough = gsub(pattern = "Franklin|Clinton|Essex/Hamilton|Hamilton/Essex", replacement = "Eastern Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Herkimer|Jefferson|Lewis|Oneida|Oswego|St Lawrence", replacement = "Western Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Broome|Cayuga|Chenango|Cortland|Madison|Onondaga|Otsego|Tioga|Tompkins", replacement = "Central New York", borough)) %>% 
  transform(borough=gsub(pattern="Chemung|Genesee|Livingston|Monroe|Ontario|Schuyler|Seneca|Steuben|Wayne|Yates",replacement="Finger Lakes", borough)) %>% 
  transform(borough=gsub(pattern="Allegany|Cattaraugus|Chautauqua|Erie|Niagara|Orleans|Wyoming",replacement="Western New York", borough)) %>% 
  transform(borough=gsub(pattern="Delaware|Dutchess|Orange|Putnam|Sullivan|Ulster",replacement="Hudson Valley", borough)) %>% 
  transform(borough=gsub(pattern="Rockland|Westchester", replacement="Westchester/Rockland", borough)) %>% 
  transform(borough=gsub(pattern="Suffolk|Nassau", replacement="Long Island", borough)) %>% 
  group_by(borough, year) %>% 
  summarize(total_rate= sum(total))

## `summarise()` has grouped output by 'borough'. You can override using the
## `.groups` argument.

Merging

merged_2018=
  full_join(rename_lb_2018,rename_ia_2018, by="borough") %>%
  janitor::clean_names() %>%
  mutate(total = (total_rate_y / total_rate_x)*1000) %>% 
  select(total, year_x)

## Adding missing grouping variables: `borough`

Induced Abortions in Years (2017)

url = "https://www.health.ny.gov/statistics/vital_statistics/2017/table21.htm"
url1= "https://www.health.ny.gov/statistics/vital_statistics/2017/table07.htm"
induced_abortion_2017 = 
  read_html(url) %>%
  html_table(header = FALSE) %>%
  first() %>%
  janitor::clean_names()
live_birth_2017 = 
  read_html(url1) %>%
  html_table(header = FALSE) %>%
  first() %>%
  janitor::clean_names()

data cleaning

renaming counties into regions.

rename_lb_2017= clean_lb_2017 %>% 
  transform(borough = gsub(pattern = "Albany|Columbia|Fulton|Greene|Montgomery|Rensselaer|Saratoga|Schenectady|Schoharie|Warren|Washington", replacement = "Saratoga", borough)) %>%
  transform(borough = gsub(pattern = "Franklin|Clinton|Essex|Hamilton", replacement = "Eastern Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Herkimer|Jefferson|Lewis|Oneida|Oswego|St Lawrence", replacement = "Western Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Broome|Cayuga|Chenango|Cortland|Madison|Onondaga|Otsego|Tioga|Tompkins", replacement = "Central New York", borough)) %>% 
  transform(borough=gsub(pattern="Chemung|Genesee|Livingston|Monroe|Ontario|Schuyler|Seneca|Steuben|Wayne|Yates",replacement="Finger Lakes", borough)) %>% 
  transform(borough=gsub(pattern="Allegany|Cattaraugus|Chautauqua|Erie|Niagara|Orleans|Wyoming",replacement="Western New York", borough)) %>% 
  transform(borough=gsub(pattern="Delaware|Dutchess|Orange|Putnam|Sullivan|Ulster",replacement="Hudson Valley", borough)) %>% 
  transform(borough=gsub(pattern="Rockland|Westchester", replacement="Westchester/Rockland", borough)) %>% 
  transform(borough=gsub(pattern="Suffolk|Nassau", replacement="Long Island", borough)) %>% 
  group_by(borough, year) %>% 
  summarize(total_rate= sum(total))

## `summarise()` has grouped output by 'borough'. You can override using the
## `.groups` argument.

rename_ia_2017= clean_ia_2017 %>% 
  transform(borough = gsub(pattern = "Albany|Columbia|Fulton|Greene|Montgomery|Rensselaer|Saratoga|Schenectady|Schoharie|Warren|Washington", replacement = "Saratoga", borough)) %>%
  transform(borough = gsub(pattern = "Franklin|Clinton|Essex/Hamilton|Hamilton/Essex", replacement = "Eastern Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Herkimer|Jefferson|Lewis|Oneida|Oswego|St Lawrence", replacement = "Western Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Broome|Cayuga|Chenango|Cortland|Madison|Onondaga|Otsego|Tioga|Tompkins", replacement = "Central New York", borough)) %>% 
  transform(borough=gsub(pattern="Chemung|Genesee|Livingston|Monroe|Ontario|Schuyler|Seneca|Steuben|Wayne|Yates",replacement="Finger Lakes", borough)) %>% 
  transform(borough=gsub(pattern="Allegany|Cattaraugus|Chautauqua|Erie|Niagara|Orleans|Wyoming",replacement="Western New York", borough)) %>% 
  transform(borough=gsub(pattern="Delaware|Dutchess|Orange|Putnam|Sullivan|Ulster",replacement="Hudson Valley", borough)) %>% 
  transform(borough=gsub(pattern="Rockland|Westchester", replacement="Westchester/Rockland", borough)) %>% 
  transform(borough=gsub(pattern="Suffolk|Nassau", replacement="Long Island", borough)) %>% 
  group_by(borough, year) %>% 
  summarize(total_rate= sum(total))

## `summarise()` has grouped output by 'borough'. You can override using the
## `.groups` argument.

Merging

merged_2017=
  full_join(rename_lb_2017,rename_ia_2017, by="borough") %>%
  janitor::clean_names() %>%
  mutate(total = (total_rate_y / total_rate_x)*1000) %>% 
  select(total, year_x)

## Adding missing grouping variables: `borough`

Induced Abortions in Years (2016)

url = "https://www.health.ny.gov/statistics/vital_statistics/2016/table21.htm"
url1= "https://www.health.ny.gov/statistics/vital_statistics/2016/table07.htm"
induced_abortion_2016= 
  read_html(url) %>%
  html_table(header = FALSE) %>%
  first() %>%
  janitor::clean_names()
live_birth_2016= 
  read_html(url1) %>%
  html_table(header = FALSE) %>%
  first() %>%
  janitor::clean_names()

data cleaning

renaming counties into regions.

rename_lb_2016= clean_lb_2016 %>% 
  transform(borough = gsub(pattern = "Albany|Columbia|Fulton|Greene|Montgomery|Rensselaer|Saratoga|Schenectady|Schoharie|Warren|Washington", replacement = "Saratoga", borough)) %>%
  transform(borough = gsub(pattern = "Franklin|Clinton|Essex|Hamilton", replacement = "Eastern Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Herkimer|Jefferson|Lewis|Oneida|Oswego|St Lawrence", replacement = "Western Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Broome|Cayuga|Chenango|Cortland|Madison|Onondaga|Otsego|Tioga|Tompkins", replacement = "Central New York", borough)) %>% 
  transform(borough=gsub(pattern="Chemung|Genesee|Livingston|Monroe|Ontario|Schuyler|Seneca|Steuben|Wayne|Yates",replacement="Finger Lakes", borough)) %>% 
  transform(borough=gsub(pattern="Allegany|Cattaraugus|Chautauqua|Erie|Niagara|Orleans|Wyoming",replacement="Western New York", borough)) %>% 
  transform(borough=gsub(pattern="Delaware|Dutchess|Orange|Putnam|Sullivan|Ulster",replacement="Hudson Valley", borough)) %>% 
  transform(borough=gsub(pattern="Rockland|Westchester", replacement="Westchester/Rockland", borough)) %>% 
  transform(borough=gsub(pattern="Suffolk|Nassau", replacement="Long Island", borough)) %>% 
  group_by(borough, year) %>% 
  summarize(total_rate= sum(total))

## `summarise()` has grouped output by 'borough'. You can override using the
## `.groups` argument.

rename_ia_2016= clean_ia_2016 %>% 
  transform(borough = gsub(pattern = "Albany|Columbia|Fulton|Greene|Montgomery|Rensselaer|Saratoga|Schenectady|Schoharie|Warren|Washington", replacement = "Saratoga", borough)) %>%
  transform(borough = gsub(pattern = "Franklin|Clinton|Essex/Hamilton|Hamilton/Essex", replacement = "Eastern Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Herkimer|Jefferson|Lewis|Oneida|Oswego|St Lawrence", replacement = "Western Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Broome|Cayuga|Chenango|Cortland|Madison|Onondaga|Otsego|Tioga|Tompkins", replacement = "Central New York", borough)) %>% 
  transform(borough=gsub(pattern="Chemung|Genesee|Livingston|Monroe|Ontario|Schuyler|Seneca|Steuben|Wayne|Yates",replacement="Finger Lakes", borough)) %>% 
  transform(borough=gsub(pattern="Allegany|Cattaraugus|Chautauqua|Erie|Niagara|Orleans|Wyoming",replacement="Western New York", borough)) %>% 
  transform(borough=gsub(pattern="Delaware|Dutchess|Orange|Putnam|Sullivan|Ulster",replacement="Hudson Valley", borough)) %>% 
  transform(borough=gsub(pattern="Rockland|Westchester", replacement="Westchester/Rockland", borough)) %>% 
  transform(borough=gsub(pattern="Suffolk|Nassau", replacement="Long Island", borough)) %>% 
  group_by(borough, year) %>% 
  summarize(total_rate= sum(total))

## `summarise()` has grouped output by 'borough'. You can override using the
## `.groups` argument.

Merging

merged_2016=
  full_join(rename_lb_2016,rename_ia_2016, by="borough") %>%
  janitor::clean_names() %>%
  mutate(total = (total_rate_y / total_rate_x)*1000) %>% 
  select(total, year_x)

## Adding missing grouping variables: `borough`

Induced Abortions in Years (2015)

url = "https://www.health.ny.gov/statistics/vital_statistics/2015/table21.htm"
url1 = "https://www.health.ny.gov/statistics/vital_statistics/2015/table07.htm"
induced_abortion_2015 = 
  read_html(url) %>%
  html_table(header = FALSE) %>%
  first() %>%
  janitor::clean_names()
live_birth_2015 = 
  read_html(url1) %>%
  html_table(header = FALSE) %>%
  first() %>%
  janitor::clean_names()

data cleaning

renaming counties into regions.

rename_lb_2015= clean_lb_2015 %>% 
  transform(borough = gsub(pattern = "Albany|Columbia|Fulton|Greene|Montgomery|Rensselaer|Saratoga|Schenectady|Schoharie|Warren|Washington", replacement = "Saratoga", borough)) %>%
  transform(borough = gsub(pattern = "Franklin|Clinton|Essex|Hamilton", replacement = "Eastern Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Herkimer|Jefferson|Lewis|Oneida|Oswego|St Lawrence", replacement = "Western Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Broome|Cayuga|Chenango|Cortland|Madison|Onondaga|Otsego|Tioga|Tompkins", replacement = "Central New York", borough)) %>% 
  transform(borough=gsub(pattern="Chemung|Genesee|Livingston|Monroe|Ontario|Schuyler|Seneca|Steuben|Wayne|Yates",replacement="Finger Lakes", borough)) %>% 
  transform(borough=gsub(pattern="Allegany|Cattaraugus|Chautauqua|Erie|Niagara|Orleans|Wyoming",replacement="Western New York", borough)) %>% 
  transform(borough=gsub(pattern="Delaware|Dutchess|Orange|Putnam|Sullivan|Ulster",replacement="Hudson Valley", borough)) %>% 
  transform(borough=gsub(pattern="Rockland|Westchester", replacement="Westchester/Rockland", borough)) %>% 
  transform(borough=gsub(pattern="Suffolk|Nassau", replacement="Long Island", borough)) %>% 
  group_by(borough, year) %>% 
  summarize(total_rate= sum(total))

## `summarise()` has grouped output by 'borough'. You can override using the
## `.groups` argument.

rename_ia_2015= clean_ia_2015 %>% 
  transform(borough = gsub(pattern = "Albany|Columbia|Fulton|Greene|Montgomery|Rensselaer|Saratoga|Schenectady|Schoharie|Warren|Washington", replacement = "Saratoga", borough)) %>%
  transform(borough = gsub(pattern = "Franklin|Clinton|Essex/Hamilton|Hamilton/Essex", replacement = "Eastern Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Herkimer|Jefferson|Lewis|Oneida|Oswego|St Lawrence", replacement = "Western Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Broome|Cayuga|Chenango|Cortland|Madison|Onondaga|Otsego|Tioga|Tompkins", replacement = "Central New York", borough)) %>% 
  transform(borough=gsub(pattern="Chemung|Genesee|Livingston|Monroe|Ontario|Schuyler|Seneca|Steuben|Wayne|Yates",replacement="Finger Lakes", borough)) %>% 
  transform(borough=gsub(pattern="Allegany|Cattaraugus|Chautauqua|Erie|Niagara|Orleans|Wyoming",replacement="Western New York", borough)) %>% 
  transform(borough=gsub(pattern="Delaware|Dutchess|Orange|Putnam|Sullivan|Ulster",replacement="Hudson Valley", borough)) %>% 
  transform(borough=gsub(pattern="Rockland|Westchester", replacement="Westchester/Rockland", borough)) %>% 
  transform(borough=gsub(pattern="Suffolk|Nassau", replacement="Long Island", borough)) %>% 
  group_by(borough, year) %>% 
  summarize(total_rate= sum(total))

## `summarise()` has grouped output by 'borough'. You can override using the
## `.groups` argument.

Merging

merged_2015=
  full_join(rename_lb_2015,rename_ia_2015, by="borough") %>%
  janitor::clean_names() %>%
  mutate(total = (total_rate_y / total_rate_x)*1000) %>% 
  select(total, year_x)

## Adding missing grouping variables: `borough`

Induced Abortions in Years (2014)

url = "https://www.health.ny.gov/statistics/vital_statistics/2014/table21.htm"
url1 = "https://www.health.ny.gov/statistics/vital_statistics/2014/table07.htm"
induced_abortion_2014 = 
  read_html(url) %>%
  html_table(header = FALSE) %>%
  first() %>%
  janitor::clean_names()
live_birth_2014 = 
  read_html(url1) %>%
  html_table(header = FALSE) %>%
  first() %>%
  janitor::clean_names()

data cleaning

Renaming

renaming counties into regions.

rename_lb_2014= clean_lb_2014 %>% 
  transform(borough = gsub(pattern = "Albany|Columbia|Fulton|Greene|Montgomery|Rensselaer|Saratoga|Schenectady|Schoharie|Warren|Washington", replacement = "Saratoga", borough)) %>%
  transform(borough = gsub(pattern = "Franklin|Clinton|Essex|Hamilton", replacement = "Eastern Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Herkimer|Jefferson|Lewis|Oneida|Oswego|St Lawrence", replacement = "Western Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Broome|Cayuga|Chenango|Cortland|Madison|Onondaga|Otsego|Tioga|Tompkins", replacement = "Central New York", borough)) %>% 
  transform(borough=gsub(pattern="Chemung|Genesee|Livingston|Monroe|Ontario|Schuyler|Seneca|Steuben|Wayne|Yates",replacement="Finger Lakes", borough)) %>% 
  transform(borough=gsub(pattern="Allegany|Cattaraugus|Chautauqua|Erie|Niagara|Orleans|Wyoming",replacement="Western New York", borough)) %>% 
  transform(borough=gsub(pattern="Delaware|Dutchess|Orange|Putnam|Sullivan|Ulster",replacement="Hudson Valley", borough)) %>% 
  transform(borough=gsub(pattern="Rockland|Westchester", replacement="Westchester/Rockland", borough)) %>% 
  transform(borough=gsub(pattern="Suffolk|Nassau", replacement="Long Island", borough)) %>% 
  group_by(borough, year) %>% 
  summarize(total_rate= sum(total))

## `summarise()` has grouped output by 'borough'. You can override using the
## `.groups` argument.

rename_ia_2014= clean_ia_2014 %>% 
  transform(borough = gsub(pattern = "Albany|Columbia|Fulton|Greene|Montgomery|Rensselaer|Saratoga|Schenectady|Schoharie|Warren|Washington", replacement = "Saratoga", borough)) %>%
  transform(borough = gsub(pattern = "Franklin|Clinton|Essex/Hamilton|Hamilton/Essex", replacement = "Eastern Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Herkimer|Jefferson|Lewis|Oneida|Oswego|St Lawrence", replacement = "Western Adirondacks", borough)) %>%
  transform(borough = gsub(pattern = "Broome|Cayuga|Chenango|Cortland|Madison|Onondaga|Otsego|Tioga|Tompkins", replacement = "Central New York", borough)) %>% 
  transform(borough=gsub(pattern="Chemung|Genesee|Livingston|Monroe|Ontario|Schuyler|Seneca|Steuben|Wayne|Yates",replacement="Finger Lakes", borough)) %>% 
  transform(borough=gsub(pattern="Allegany|Cattaraugus|Chautauqua|Erie|Niagara|Orleans|Wyoming",replacement="Western New York", borough)) %>% 
  transform(borough=gsub(pattern="Delaware|Dutchess|Orange|Putnam|Sullivan|Ulster",replacement="Hudson Valley", borough)) %>% 
  transform(borough=gsub(pattern="Rockland|Westchester", replacement="Westchester/Rockland", borough)) %>% 
  transform(borough=gsub(pattern="Suffolk|Nassau", replacement="Long Island", borough)) %>% 
  group_by(borough, year) %>% 
  summarize(total_rate= sum(total))

## `summarise()` has grouped output by 'borough'. You can override using the
## `.groups` argument.

Merging

merged_2014=
  full_join(rename_lb_2014,rename_ia_2014, by="borough") %>%
  janitor::clean_names() %>%
  mutate(total = (total_rate_y / total_rate_x)*1000) %>% 
  select(total, year_x)

## Adding missing grouping variables: `borough`

Final Merge

Merge all datasets

merged_data=
bind_rows(merged_2019, merged_2018, merged_2017, merged_2016, merged_2015, merged_2014) %>% 
  rename(year=year_x)

Line chart by Year and Borough

plot_borough_year=merged_data %>% 
  mutate(borough = fct_reorder(borough, total)) %>% 
plot_ly(y = ~total, x=~year, color = ~borough, type = "scatter", mode="line", colors = "viridis") %>% 
   layout(title = 'Induced Abortions Year by Borough', yaxis = list(title = 'Number of Induced Abortions per 1,000 Live Births'))
plot_borough_year